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| Criterion |  Decision Making Decision Tree |  Product Discovery MVP Test Matrix |  Innovation Design Sprint |  Product Discovery Fake Door Test |
|---|---|---|---|---|
Purposedifferent | For decisions with follow-on paths and dependencies, a linear comparison is often not enough. A Decision Tree shows how options branch under conditions and which consequences hang on each branch. | When several minimal variants compete to answer the same question, it makes comparing and choosing between them cleaner. It separates problem, assumption, solution, and evidence. The result is captured as a Test Matrix and a Test Plan. | When the product question is unclear and time pressure is high, the method takes a team from an open idea to a testable solution. It connects problem understanding, decision, and learning in one compact format, lowering the risk of spending a lot of energy on a mere guess. | When demand is still unclear, it measures interest in a feature before it is built. It separates real behavior from polite agreement and deliberately keeps build effort small. |
Complexitydifferent | Medium | Medium | High | Medium |
Timedifferent | 30-90 min | 45-75 min | 4-5 Tage | 1-5 Tage |
Participantsdifferent | 1-6 | 2-8 | 5-8 | Nutzertraffic |
Formatdifferent | Workshop + async | Workshop | Workshop | Async |
Outputdifferent | Decision Tree, Option Map, Assumption List | Test Matrix, Test Plan | Prototype, Test Findings, Decision Rationale | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | DecisionTreeOptions | ExperimentsValidationDiscoveryOptions | Design sprintPrototypeValidationInnovation | ValidationExperimentsDemandDiscovery |